• 센서학회지
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• 제31권1호
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• pp.64-68
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• 2022

Herein, we propose a LoRaWAN-based small draft system that can measure the ocean current flow (speed, direction, and distance) in real time at the request of the Coast Guard to develop a device that can promptly find survivors at sea. This system has been implemented and verified in the early stages of rescue after maritime vessel accidents, which are frequent. GPS signals often transmit considerable errors, so correction algorithms using the improved triangulation method algorithm are required to accurately indicate the direction of currents in real time. This paper is structured in the following manner. The introduction section elucidates rescue activities in the case of a maritime accident. Chapter 2 explains the characteristics and main parameters of the GPS surveying technique and LoRaWAN communication, which are related studies. It explains and expands on the critical distance error correction algorithm for GPS signals and its improvement. Chapter 3 discusses the design and analysis of small draft buoys. Chapter 4 presents the testing and validation of the implemented system in both onshore and offshore environments. Finally, Section 5 concludes the study with the expected impact and effects in the future.

• Journal of the Korean Statistical Society
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• 제28권1호
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• pp.93-106
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• 1999

In this paper we consider estimation of a real valued parameter in the drift coefficient of a Hilbert space valued Ito stochastic differential equation. First we consider observation of the corresponding diffusion in a fixed time interval [0, T] and prove the Bernstein - von Mises theorem concerning the convergence of posterior distribution of the parameter given the observation, suitably normalised and centered at the MLE, to the normal distribution as Tlongrightarrow$\infty$. As a consequence, the Bayes estimator of the drift parameter becomes asymptotically efficient and asymptotically equivalent to the MLE as Tlongrightarrow$\infty$. Next, we consider observation in a random time interval where the random time is determined by a predetermined level of precision. We show that the sequential MLE is better than the ordinary MLE in the sense that the former is unbiased, uniformly normally distributed and efficient but is latter is not so.

• 한국주조공학회지
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• 제26권3호
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• pp.129-132
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• 2006

In the present study the new method was proposed by using the real-time X-ray observation and metal die in order to evaluate fluidity and viscosity of the molten metal during pouring into the mold. The special mold for the present experiment was introduced since X-ray could not transmit thick mold wall and scatter the image of the molten metal during pouring. The present study also discussed for evaluation of viscosities by using the flow data from radioscopy images, and the viscosities of six commercial aluminum alloys were evaluated and compared.

• 한국지구과학회지
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• 제30권4호
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• pp.478-484
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• 2009

본 연구에서는 자동기상관측시스템(AWS)을 이용하여 기상요소의 관측 자료를 수집하고 실시간으로 그 자료를 제공하는 웹 페이지를 개발하였다. 이 시스템은 실시간으로 자료를 제공하면서 동시에 데이터베이스(DB)로 누적하여, 사용자의 요청에 따라 과거의 기상 자료를 파일로 제공하는 기능도 있다. 완성된 페이지를 이용하여 학교 현장에서 지구과학 교과의 기상분야 탐구학습에 성공적으로 활용하였다. 이 연구 결과, 기상 관측 자료를 실시간으로 제공함으로써 기상 분야 탐구학습의 현장감을 높일 수 있게 되었다. 또 누적된 과거 기상 자료를 이용함으로써 시간규모가 너무 길어서 실질적인 탐구학습이 어렵던 지구과학 교과의 제약을 일부 극복하게 되었다.

• Journal of Advanced Marine Engineering and Technology
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• 제35권5호
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• pp.682-689
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• 2011

최근 우리나라 해안지역에서는 너울성 파도(Swell-like wave)에 의한 재해가 빈번하게 발생하고 있다. 이러한 해양 현상은 풍파(wind wave)에 비해 주기가 10초대 이상의 긴 주기를 갖는 특성이 있다. 장주기 파(Long period wave)에 의한 피해를 사전에 예방하기 위해서는 실시간으로 정확하게 관측할 수 있어야 한다. 하지만 현재 파고를 측정하는 기기는 풍파를 관측하는 것을 주 목적으로 하고 있어 장주기 파를 관측할 수가 없다. 따라서 본 연구에서는 GPS를 이용하여 해양에서 실시간으로 운영할 수 있는 장주기 파고 관측시스템을 개발하고자 하는 것이다.

• 해양환경안전학회지
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• 제5권1호
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• pp.9-18
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• 1999

To predict the oil spill dispersion phenomena in the ocean, the oil spill response model, which can be used for strategic purpose on the oil spill site, based on Lagrangian particle-tracking method was formulated and applied to the neighboring area with Pusan port where the oil spill incident occurred when the tanker ship No.1 Youil struck on a small rock near the Namhyungjeto on September 21, 1995. The real-time tidal currents to be required as input data of the oil spill model were obtained by the two-dimensional hydrodynamic model and the tide prediction model. Evaluation of tidal currents using observation data was successful. For wind data, other input data of oil spill model, observed data on the spot were used. To verify the oil spill model, the oil spill modelling results were compared with the field data obtained from the spill site. Compared the modelling results with the observation data, there exist some discrepancies but the general pattern of modelling results was similar to that of field observation. The modelling results on 7 days after spill occurred showed that the 40% of spilled oil is in floating, 36% in evaporated, 23% at shore, and 1% in out of boundary, respectively. According to the evaluation of weighting curves of effective components to the dispersion of oil, the winds make a 37% of contribution to the dispersion of oil, turbulent diffusion 39.5%, and tidal currents 23.5%, respectively. Provided the more accurate wind data are supported, more favorable results might be obtained.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.150-150
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• 2018

The Numerical Weather Prediction (NWP) models provide information for weather forecasts. The highly nonlinear and complex interactions in the atmosphere are simplified in meteorological models through approximations and parameterization. Therefore, the simplifications may lead to biases and errors in model results. Although the models have improved over time, the biased outputs of these models are still a matter of concern in meteorological and hydrological studies. Thus, bias removal is an essential step prior to using outputs of atmospheric models. The main idea of statistical bias correction methods is to develop a statistical relationship between modeled and observed variables over the same historical period. The Model Output Statistics (MOS) would be desirable to better match the real time forecast data with observation records. Statistical post-processing methods relate model outputs to the observed values at the sites of interest. In this study three methods are used to remove the possible biases of the real-time outputs of the Weather Research and Forecast (WRF) model in Imjin basin (North and South Korea). The post-processing techniques include the Linear Regression (LR), Linear Scaling (LS) and Power Scaling (PS) methods. The MOS techniques used in this study include three main steps: preprocessing of the historical data in training set, development of the equations, and application of the equations for the validation set. The expected results show the accuracy improvement of the real-time forecast data before and after bias correction. The comparison of the different methods will clarify the best method for the purpose of the forecast skill enhancement in a real-time case study.

• 한국농림기상학회지
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• 제22권3호
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• pp.117-127
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• 2020

농촌진흥청 농업기상재해 조기경보시스템은 기상청으로부터 제공되는 기상정보를 활용하여 농장 단위로 상세 추정하고, 추정된 상세 기상정보를 바탕으로 작물의 생육 추정 및 생육이 진행됨에 따라 발생할 수 있는 기상 재해를 예측하여 사용자에게 미리 전달한다. 이들 예측 정보를 검증하기 위한 무인기상관측망을 연구 지역 내에 구축하였으며, 관측망으로부터 수집되는 기상 실황 자료의 실시간 웹 표출 시스템을 구축하였다. 기상관측장비로부터 수집되는 기상요소로는 기온, 습도, 일사량, 강우량, 토양수분, 일조시간, 풍속, 풍향 등이며, 1분단위로 수집 및 10분 간격으로 서버로 전송된다. 자료 표출 시스템은 기상관측장비로 부터 수집되는 1분 단위의 기상자료를 DB로 구축하는 1단계, 수집된 기상자료를 10분, 1시간, 1일 단위로 통계 분석하는 2단계, 수집 및 분석한 기상자료를 웹으로 표출하는 3단계로 구성된다. DB에 수집된 기상자료는 웹 페이지를 통해, 전체 지점 또는 1개 지점의 1분단위, 10분단위, 1시간 단위, 1일 단위로 조회할 수 있으며, CSV 포맷으로 다운로드 할 수 있다. 자료 표출 시스템 접속 URL은 http://aws.agmet.kr 이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.488-491
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• 1988

In this work, we developed a real-time versatile advanced control and supervisory software for a personal computer control. This software, basically, has background and foreground tasks which are performed in parallel at real time. First, background tasks are composed of controls of various kinds, reports and input-ouput of signals etc, which are performed every sampling time. Second, foreground tasks are observation of operation conditions, data search, regulation of controllers and graphical design and display of processes, which are performed by users request. Additionally, this software has the functions of transporting data and composing distributed control systems, and all background tasks are composed of combination of unit function blocks.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1419-1424
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• 2018

Very short-term electric load forecasting is essential for real-time power system operation. In this paper, a very short-term electric load forecasting technique applying the Kalman filter algorithm is proposed. In order to apply the Kalman filter algorithm to electric load forecasting, an electrical load forecasting algorithm is defined as an observation model and a state space model in a time domain. In addition, in order to precisely reflect the noise characteristics of the Kalman filter algorithm, the optimal error covariance matrixes Q and R are selected from several experiments. The proposed algorithm is expected to contribute to stable real-time power system operation by providing a precise electric load forecasting result in the next six hours.